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Long-term morphodynamics of
muddy backbarrier basins:
the relative importance of lateral
bank erosion and vertical platform drowning.
Alberto Canestrelli
University of Florida
Giulio Mariotti
Louisiana State University
Back-barrier systems are sheltered basins located
behind barriers which are parallel to the coast.
Salt marshes form mud is allowed to deposit.
Virginia Coast Reserve
3 – Long term evolution of back-barrier ecosystems: fill in or empty out?
Approximately half of US salt marshes are
located along the Gulf Coast.
Salt marshes are the most productive ecosystem known.
Filters out toxins from incoming water.
Accumulate organic material with time, forming a dense
layer called peat.
Important sinks for atmospheric CO2
Act as effective storm buffer and effective sediment trap
- withstanding large wave forces with no significant vertical erosion
Moller et al. (2014)
Allen and Haslett. (2014)
Marsh progradationMarsh retreat
3 – Long term evolution of back-barrier ecosystems: fill in or empty out?
Can marshes withstand high rates of SLR and be in morphodynamic equilibrium?1
2 Are marshes eroding by drowning or horizontal retreat?
Marsh erosion versus progradation
Organic and inorg. deposition versus SLR
Mariotti and Carr, 2014
3 – Long term evolution of back-barrier ecosystems: fill in or empty out?
ISSUES OF CLASSICAL/SIMPLE BANK EROSION APPROACH
(SUCH AS THE ONE EMPLOYED IN DELFT3D)
BANK EROSION VERTICAL BANK DISPLACEMENT=
Very low
velocity/wave
energy
No further
erosion
Canestrelli et. al.,2016
High velocity/wave
energy close to the
bank.
=> Bank retreat
Analytical solution
Simplified approach
𝑝 Δ𝑡𝑖 =
𝛹 𝑘
𝐴
𝑙 𝑘
𝑘
𝐴: area
Marsh
𝛹 𝑘
𝑙 𝑘
𝐴: area
Suspended Sediment Concentration of mud co [mg/l]
- Rate of Relative sea level rise (R)
-Wind distribution:
Wind speed [m/s]
3 – Long term evolution of back-barrier ecosystems: fill in or empty out?
-Landward transgression not possible due to the
presence of human settlements and infrastructure
along the coastline (Doody, Coastal squeeze, 2004).
- The barrier island is fixed in time seawalls:
SWAN
MODEL
Tide: 2 m mean tidal range, spring-neap
Marsh edge erosion
E = α P
Wave powerRetreat rate
Validated with field data (Leonardi et al., 2016)
3 – Long term evolution of back-barrier ecosystems: fill in or empty out?
Dorg = Korg
B
Bmax
Marsh vegetation processes:
• Biomass is a parabolic function of inundation depth
• Organic sediment production prop. to biomass:
• Increase in drag
• Increase in critical shear stress
Morris et al, 2013
MSL MHW
co = 0 mg/l
R = 1 mm/yr
SAND vs MUD
3 – Long term evolution of back-barrier ecosystems: fill in or empty out?
Bassin d’Arcagnon (France)
NO WIND
WIND
Formation of marshes (R = 1 mm/yr)
co = 0 mg/l co = 50 mg/l
2 km
At equilibrium:
Marsh extent is
~70% of the basin
Virginia Georgia
3 – Long term evolution of back-barrier ecosystems: fill in or empty out?
TIDE
+
WAVE
Mud: Mud:
R=10 mm/y
Which concentration do I need to
withstand a R=10 mm/y
3 – Long term evolution of back-barrier ecosystems: fill in or empty out?
What happens if I cut
out sediment input?
C0=0R=1mm/y
Bad news:
Marsh retreat increases with R
Because sediment needs to fill accommodation space,
less available for marsh progradation
Because marsh edge perimeter decreases
Basin-wide marsh edge erosion slows down
as the marsh erodes away
Good news:
3 – Long term evolution of back-barrier ecosystems: fill in or empty out?
3 – Long term evolution of back-barrier ecosystems: fill in or empty out?
Marsh does not drown
for R up to 10 mm/yr
even without external
sediment supply!
Good news:
Because of internal
sediment recycle
With SLR <5 mm/yr, such as those
currently experienced in the US
Atlantic Coast, marsh retreat is a
more likely modality of marsh loss
than marsh drowning!!
Bank erosion PREVENTS DRAWNING!
3 – Long term evolution of back-barrier ecosystems: fill in or empty out?
Open issues:
How is this picture changing with river inflow?
How does the picture change when the boundaries are not fixed:
-barrier can be overtopped and transgresses over the
salt marshes
Kirwan, 2016
-marshes can migrate inland
Raabe and stumf, 2016
Overwash resolving wave model
Take-home message
• Edge erosion “empties” backbarrier basins
• Retreat slowed down and reversed by external sediment
supply, which promotes marsh progradation
• Internal sediment recycle allow marsh to accrete vertically
even in the absence of external sediment supply
= • Sea level rise increases the rate of marsh retreat
3 – Long term evolution of back-barrier ecosystems: fill in or empty out?
Low to moderate SLR(<5 mm/yr), such as those currently experienced in the US Atlantic Coast
(Engelhart et al., 2009), marsh retreat is a more likely modality of marsh loss than marsh drowning!!
• If no/low external sediment, basin can empty also with no SLR
• “Filled basin” dynamic equilibrium with large channels
SUPPLEMENTARY MATERIAL
MARSHES
• Low gradient of shelf
• Abundant sediment supply
• Low tidal energy with respect to wave energy
3 – Long term evolution of back-barrier ecosystems: fill in or empty out?
How do barrier islands form?
How does the picture change when salt marshes form in open
ocean, like at Florida Big Bend?
Improving ecological coupling
Modeling multi-species and zonation
(spartinas ,needlerush, mangroves)
Storing vertical stratigraphy Peat formation
(Petroleum
Research Fund)
This effect could explain why marsh edge erosion in the
Mississippi Delta (LA), a region with very high rates
of sea level rise (and subsidence), can be as fast as 10
m/yr [Penland et al., 2002], a rate that is several times
faster than in other eroding marshes within the U.S.
[Mariotti and Fagherazzi, 2013b; McLoughlin et al.,
2014]
Wave versus tidally dominated
Bank erosion prevents drowning!!!
Marsh edge erosion, mudflat deepening, and channel deepening release sediments (Figure 10)
[Day et al., 1998]. Furthermore, marsh edge erosion increases the mudflat area, which could
be then eroded by surface erosion from bed shear stress. The model predicts that wave
erosion would increase the suspended sediment concentration in the mudflat to 100–200
mg/L, which agrees with field measurements in the backbarrier basins of the Virginia Coast
Reserve (VA, USA) [Lawson et al., 2007].
Even when the marsh enters the runaway erosion and eventually disappears, the marsh platform keeps
pace with sea level rise up to 10 mm/yr, i.e., marsh loss by drowning does not take place. Of particular
notice is that the marsh platform keeps up even in the absence of an external sediment supply (co50). In
this case, because the maximum accretion rate by organic sediment was set equal to 5 mm/yr, inorganic
sediment contributed to 5 mm/yr of accretion or more. If only organic sediment were contributing to vertical
accretion, a marsh starting at MHW (here set 1 m above msl) would have drown in 157 years considering
a parabolic biomass-elevation relationship (see section 2.2) (Figure 9g). Where did the additional sediment
come from if the external sediment concentration was zero? Clearly these sediment resulted from erosion
of the basin, i.e., by internal recycling
Equilibrium:
ebb dominated currents
that establish in channels with extensive intertidal areas
No tidal flats => no marsh progradation
remarkably similar, especially considering that the wave
forcing is stochastic
MF=400
However, this formulation fails to reproduce the expected marsh edge
retreat for a given wave power (equation (5)). For example,
such a formulation predicts a fast (slow) edge retreat when the mudflat
in front of the marsh is shallow
deep), given that bed shear stress of locally generated
waves decreases with water depth [Fagherazzi et al., 2006].
In reality, a faster marsh retreat is expected where the marsh
edge faces a deeper mudflat, which would allow a larger
wave power to reach the marsh edge.
The ability of marshes to reduce sediment erodability and increase drag is simulated in a simplified way: if a
cell is unvegetated the critical shear stress for erosion is set equal to scr,unveg and the Chezy coefficient for
bed friction is set equal to Cunveg, if a cell is vegetated the critical shear stress is set equal to scr,veg and the
Chezy coefficient is set equal to Cveg. Here we set the vegetated critical shear stress equal to 1 Pa, noticing
that values above 0.8 Pa are already sufficient to make the soil virtually nonerodible [Marani et al., 2010].
This choice is consistent with the observation that the marsh platform is able to withstand large wave forces
[M€oller, 2006].
s range from 2.5 mm/yr [D’Alpaos et al., 2007] to 10
mm/yr [Blum and Christian,
2004
The wave power
causing marsh retreat is calculated on the unvegetated
cell facing a marsh boundary cell as
c is the specific weight of the water, Hs is the significant wave height, and cg is the wave group velocity,
which are obtained from the SWAN model.
marsh edge erosion is complex and poorly understood and includes a variety of masswasting
geotechnical processes such as undercutting and cantilever failure, toppling failure, and stress
failure, as well as hydrodynamic processes that occur at small spatial scales (0.1–1 m), such as wave
breaking and dissipation over the edge [Schwimmer, 2001; McLoughlin et al., 2014; Priestas et al., 2015;
Bendoni et al., 2016]. For simplicity, the effect of these processes are lumped into an empirical coefficient
aw, which is highly variable, site specific, and not predictable a priori. Rather than selecting a value that
fits a specific field site, we choose a value that gives marsh retreat rates on the order of a meter per year
(see section 3.4), in range with field measurements
Because of the large gird size (100 m) and the relatively small time step (2 min), the probability p is at most
1024
For the U.S. Atlantic Coast, organic matter contributes to about 50% to
vertical accretion [Morris et al., 2016], therefore, we used a rounded value and set fox to 50% in our model
Average marsh retreat rate during the first 100 years for
the three rates of sea level rise. Given that the areal
retreat rate is about
0.1 km2/yr for R51 mm/yr, 0.2 km2/yr for R55 mm/yr, and
0.4 km2/yr for R510 mm/yr (Figure 9a), and
given that the total marsh edge perimeter during the same
time is about 300 km (supporting information
Figure S4),
Thriving along protected shorelines, they are a common
habitat in the U.S., where salt marshes can be found on
every coast. Approximately half of the nation's salt
marshes are located along the Gulf Coast.
Salt marshes are coastal wetlands that are flooded and
drained by salt water brought in by the tides. They are
marshy because the soil may be composed of deep mud
and peat.
Back-barrier systems are coastal basins who are
protected from storm by mean of barriers which are
parallel to the coast.
Salt marshes form in these relatively quiet environments,
in which mud is allowed to deposit.
Virginia Coast Reserve
3 – Long term evolution of back-barrier ecosystems: fill in or empty out?
IMPORTANCE OF SALT MARSHES
3 – Long term evolution of back-barrier ecosystems: fill in or empty out?
“The salt marsh is the most productive ecosystem
known. Grasses, algae, and phyto-plankton can
produce up to 10 tons of organic matter per acre per
year. …Because more organic matter is produced
than is used by salt marsh inhabitants, this community
is continually exporting nutrients … enriching the
surrounding estuary. The importance of the salt marsh
to marine ecosystems cannot be overemphasized.”
Janet McMahon in: “Forests, Fields, and Estuaries:
A Guide to the Natural Communities of Josephine
Newman Sanctuary”
IMPORTANCE OF SALT MARSHES
Act as effective storm buffer
- withstand large wave forces with no significant vertical erosion
- a reduction in wave height of 20% after crossing 40 metres.
- Effective sediment trap
In places where marshes have been destroyed, winter storms
are more damaging.
Erosive nature of tides is also dampened by wetland plants
Tides carry in nutrients that stimulate plant growth in the marsh and carry out
organic material that feeds fish and other coastal organisms
Ability to filter out and break down toxins and sediments from
incoming water.
3 – Long term evolution of back-barrier ecosystems: fill in or empty out?
Salt marshes are important sinks for atmospheric CO2
Over time, salt marshes accumulate organic material,
forming into a dense layer called peat.
Moller et al. (2014)
Zonation
Low Marsh
Highmarsh
Distribution of Salt Marshes
3 – Salt marshes SUPPLEMENTARY MATERIAL
Values of Korg used in previous models range from 2.5 mm/yr [D’Alpaos et al.,
2007] to 10 mm/yr [Blum and Christian, 2004], here we choose an
intermediate value of 5 mm/yr.
3 – Marshes SUPPLEMENTARY MATERIAL
if a cell is unvegetated the critical shear stress for erosion is set equal to τcr,unveg and the Chezy coefficient for
bed friction is set equal to Cunveg, if a cell is vegetated the critical shear stress is set equal to τcr,veg and the
Chezy coefficient is set equal to Cveg. Here we set the vegetated critical shear stress equal to 1 Pa, noticing that
values above 0.8 Pa are already sufficient to make the soil virtually nonerodible [Marani et al., 2010]. Such
choice is consistent with the observation that the marsh platform is able to withstand large wave forces
[Möller, 2006
𝑊 = 1 16 𝛾𝑐 𝑔 𝐻𝑠
2
" for conditions typical of the USA East Coast, organic matter probably contributes to about
60% to vertical accretion [Morris et al 2016], therefore we used a rounded value of 50%."
VALUES USED IN THE MODEL
3 – Marshes SUPPLEMENTARY MATERIAL
COMPARISON WITH LEONARDI AND FAGHERAZZI CELLULAR MODEL
Note that a probabilistic approach has also been proposed in the context of a simple
cellular automata model [Leonardi and Fagherazzi, 2014], which differs from our
approach in many aspects.
In Leonardi and Fagherazzi's approach, cells had no dimension and no bed elevation.
Eroded material was not redistributed, therefore neglecting the dissipating effect that
slumped blocks have on wave energy.
Moreover, the erosion term was divided by the erosion rates in all the exposed edge of
all the domain. This made the method global, which we think is not suitable for a
physically based model. In fact, the erosion rate of a marsh cannot depend on the
erosion rate on a different distal marsh, potentially located in a hydraulically
disconnected region of the domain.
Our method has the advantage to be local and it can be directly linked to the
deterministic approach: the expected value of the erosion with the probabilistic method
coincides with the erosion predicted with the deterministic method.
Leonardi and Fagherazzi 2014
3 – Marshes SUPPLEMENTARY MATERIAL
MODES OF MARSH EROSIONS
UndercuttingSlumping
Marsh emptying
Channel widening is caused by waves, not currents
co = 0
R = 1 mm/yr
co = 30 mg/l
R = 10 mm/yr
3 – Long term evolution of back-barrier ecosystems: fill in or empty out?
3 – Marshes SUPPLEMENTARY MATERIAL
WAVE ENERGY IN THE BASIN
Although sediment resuspension within channels is generally dominated by currents, our results show that
current-induced bed shear stress is high only in the relatively narrow channels (Fig. 12). In the wide km-wide
channels, wave-induced bed shear stress dominates, especially on channel flanks (Fig. 12). We therefore suggest
that km-wide channels are needed to generate waves large enough to trigger wave-induced sediment
resuspension.
3 – Marshes SUPPLEMENTARY MATERIAL
Synthetic time series of wind speeds
3 – Marshes SUPPLEMENTARY MATERIAL
Weibull probability distribution function for the hourly wind speed U is:
where Uo is a scale parameter and b is a form parameter.
Analysis of wind time series in the Atlantic and
Gulf coastal areas of the US gave values of 1.9–2 for the
form parameter b and 5.6–7.2 m/s for the scale
parameter [Mariotti and Fagherazzi, 2012]. For an average
wind speed of 5.76 m/s, corresponding values of 2 and 6.5
m/s for the form (distribuzione di Rayleigh) and the scale
parameter were chosen.
.
Key West: The longer term trend computed by using all the data is +2.36
mm/year.
Key west SLR
3 – Marshes SUPPLEMENTARY MATERIAL
Take-home message
• Edge erosion “empties” backbarrier basins
• Retreat slowed down and reversed by external sediment
supply, which promotes marsh progradation
• Internal sediment recycle allow marsh to accrete vertically
even in the absence of external sediment supply
= • Sea level rise increases the rate of marsh retreat
3 – Long term evolution of back-barrier ecosystems: fill in or empty out?
Low to moderate SLR(<5 mm/yr), such as those currently experienced in the US Atlantic Coast
(Engelhart et al., 2009), marsh retreat is a more likely modality of marsh loss than marsh drowning!!
• If no/low external sediment, basin can empty also with no SLR
• “Filled basin” dynamic equilibrium with large channels
3 – Long term evolution of back-barrier ecosystems: fill in or empty out?
Pagliaga salt marsh – Venice Lagoon
Tidal meanders
1932 20121970
Gaggian creek
SUPPLEMENTARY MATERIAL
SURGES
4 – Storm surge modeling and forecast
Courtesy R. Scharroo – Altimetrics LLC
Katrina: Satellite Altimeter Measurements
The Delft3D model
 =0 (water level=mean sea level) at Gibraltar
Atmospherical forcings:
ECMWF pressure fields
ECMWF Wind velocity fields
Small forecast error
Large forecast error
4 – Storm surge modeling and forecast
L
The presence of a low atmospheric
pressure event on the Northern part of
the Tyrrhenian sea results in a South-
Eastern wind (Scirocco) on the Adriatic
sea
A difference in atmospheric
pressure of 1 hPA between the two
extremities of the Adriatic sea
produces a difference in the level of
marine surface of approx. 1 cm!
Main factors for storm surge in Venice: pressure differences and winds
4 – Storm surge modeling and forecast
4 – Storm surge modeling and forecast
Forecast errors for storm larger than 50 cm
(cross validation 2010-2011)
Forecast Analysis
Lead time (h)Lead time (h)
MAE(cm)MAE(cm)
DUD (Does not use derivatives)
Delft3D is non linear!!
(Ralston and Jennrich, Dud, A Derivative-Free
Algorithm for Nonlinear Least Squares,1978)
4 – Storm surge modeling and forecast
whereas the drag coefficient depends on both wind speed and wave state
8 wind directions plus 8 velocity intervals
64
parameters
Model is strongly sensitive on the shear stress at the air-water interface
I embedded in Cd the uncertainty on the
velocity field and on Cd itself
Cd is my calibration
paramenter
The goal is to find a vector of parameters xopt that minimizes:
C
Given:
a set y of n observed data points
a model prediction fi for the ith data point.
a model with a vector x of p uncertain parameters
• Application of storm surge satellite data to the coastal protection of
Northern Cuba
Luis Cordova, F. Reale, F. Dentale, R. Lamazares, M.Buccino, E. Pugliese Carratelli …
• CUGRI (Universities of Naples &Salerno), and CUJAE (Instituto Superior Politécnico José Antonio Echeverría) of
Havana
1) Evaluating different solutions for the
protection of El Malecon (Sea front of Avana)
2) Simulating hurricane wave fields and storm
surge
3) Acquiring and assessing satellite data to
provide useful information for points 1 and 3
HurricaneIvan,2005
4– Surges - SUPPLEMENTARY MATERIAL
DUD algorithm
Take home message:
Data assimilation largely improves storm surge forecast.
An appropriate calibration of the model can remove its bias.
Satellites provide a large amount of data which have to be assimilated efficiently
in order to have real time predictions.
But we need more satellite. Now the frequence at which satellites pass over the
Adriatic Sea is once per day.
4– Surges - SUPPLEMENTARY MATERIAL

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DSD-INT 2017 Long-term morphodynamics of muddy backbarrier basins - Canestrelli

  • 1. Long-term morphodynamics of muddy backbarrier basins: the relative importance of lateral bank erosion and vertical platform drowning. Alberto Canestrelli University of Florida Giulio Mariotti Louisiana State University
  • 2. Back-barrier systems are sheltered basins located behind barriers which are parallel to the coast. Salt marshes form mud is allowed to deposit. Virginia Coast Reserve 3 – Long term evolution of back-barrier ecosystems: fill in or empty out? Approximately half of US salt marshes are located along the Gulf Coast. Salt marshes are the most productive ecosystem known. Filters out toxins from incoming water. Accumulate organic material with time, forming a dense layer called peat. Important sinks for atmospheric CO2 Act as effective storm buffer and effective sediment trap - withstanding large wave forces with no significant vertical erosion Moller et al. (2014)
  • 3. Allen and Haslett. (2014) Marsh progradationMarsh retreat 3 – Long term evolution of back-barrier ecosystems: fill in or empty out? Can marshes withstand high rates of SLR and be in morphodynamic equilibrium?1 2 Are marshes eroding by drowning or horizontal retreat? Marsh erosion versus progradation Organic and inorg. deposition versus SLR Mariotti and Carr, 2014
  • 4. 3 – Long term evolution of back-barrier ecosystems: fill in or empty out? ISSUES OF CLASSICAL/SIMPLE BANK EROSION APPROACH (SUCH AS THE ONE EMPLOYED IN DELFT3D) BANK EROSION VERTICAL BANK DISPLACEMENT= Very low velocity/wave energy No further erosion Canestrelli et. al.,2016 High velocity/wave energy close to the bank. => Bank retreat Analytical solution Simplified approach 𝑝 Δ𝑡𝑖 = 𝛹 𝑘 𝐴 𝑙 𝑘 𝑘 𝐴: area Marsh 𝛹 𝑘 𝑙 𝑘 𝐴: area
  • 5. Suspended Sediment Concentration of mud co [mg/l] - Rate of Relative sea level rise (R) -Wind distribution: Wind speed [m/s] 3 – Long term evolution of back-barrier ecosystems: fill in or empty out? -Landward transgression not possible due to the presence of human settlements and infrastructure along the coastline (Doody, Coastal squeeze, 2004). - The barrier island is fixed in time seawalls: SWAN MODEL Tide: 2 m mean tidal range, spring-neap
  • 6. Marsh edge erosion E = α P Wave powerRetreat rate Validated with field data (Leonardi et al., 2016) 3 – Long term evolution of back-barrier ecosystems: fill in or empty out? Dorg = Korg B Bmax Marsh vegetation processes: • Biomass is a parabolic function of inundation depth • Organic sediment production prop. to biomass: • Increase in drag • Increase in critical shear stress Morris et al, 2013 MSL MHW
  • 7. co = 0 mg/l R = 1 mm/yr SAND vs MUD 3 – Long term evolution of back-barrier ecosystems: fill in or empty out? Bassin d’Arcagnon (France) NO WIND WIND
  • 8. Formation of marshes (R = 1 mm/yr) co = 0 mg/l co = 50 mg/l 2 km At equilibrium: Marsh extent is ~70% of the basin Virginia Georgia 3 – Long term evolution of back-barrier ecosystems: fill in or empty out? TIDE + WAVE Mud: Mud:
  • 9. R=10 mm/y Which concentration do I need to withstand a R=10 mm/y 3 – Long term evolution of back-barrier ecosystems: fill in or empty out? What happens if I cut out sediment input? C0=0R=1mm/y
  • 10. Bad news: Marsh retreat increases with R Because sediment needs to fill accommodation space, less available for marsh progradation Because marsh edge perimeter decreases Basin-wide marsh edge erosion slows down as the marsh erodes away Good news: 3 – Long term evolution of back-barrier ecosystems: fill in or empty out?
  • 11. 3 – Long term evolution of back-barrier ecosystems: fill in or empty out? Marsh does not drown for R up to 10 mm/yr even without external sediment supply! Good news: Because of internal sediment recycle With SLR <5 mm/yr, such as those currently experienced in the US Atlantic Coast, marsh retreat is a more likely modality of marsh loss than marsh drowning!!
  • 13. 3 – Long term evolution of back-barrier ecosystems: fill in or empty out? Open issues: How is this picture changing with river inflow? How does the picture change when the boundaries are not fixed: -barrier can be overtopped and transgresses over the salt marshes Kirwan, 2016 -marshes can migrate inland Raabe and stumf, 2016 Overwash resolving wave model
  • 14. Take-home message • Edge erosion “empties” backbarrier basins • Retreat slowed down and reversed by external sediment supply, which promotes marsh progradation • Internal sediment recycle allow marsh to accrete vertically even in the absence of external sediment supply = • Sea level rise increases the rate of marsh retreat 3 – Long term evolution of back-barrier ecosystems: fill in or empty out? Low to moderate SLR(<5 mm/yr), such as those currently experienced in the US Atlantic Coast (Engelhart et al., 2009), marsh retreat is a more likely modality of marsh loss than marsh drowning!! • If no/low external sediment, basin can empty also with no SLR • “Filled basin” dynamic equilibrium with large channels
  • 16. • Low gradient of shelf • Abundant sediment supply • Low tidal energy with respect to wave energy 3 – Long term evolution of back-barrier ecosystems: fill in or empty out? How do barrier islands form? How does the picture change when salt marshes form in open ocean, like at Florida Big Bend? Improving ecological coupling Modeling multi-species and zonation (spartinas ,needlerush, mangroves) Storing vertical stratigraphy Peat formation (Petroleum Research Fund)
  • 17. This effect could explain why marsh edge erosion in the Mississippi Delta (LA), a region with very high rates of sea level rise (and subsidence), can be as fast as 10 m/yr [Penland et al., 2002], a rate that is several times faster than in other eroding marshes within the U.S. [Mariotti and Fagherazzi, 2013b; McLoughlin et al., 2014]
  • 18. Wave versus tidally dominated
  • 19.
  • 20. Bank erosion prevents drowning!!! Marsh edge erosion, mudflat deepening, and channel deepening release sediments (Figure 10) [Day et al., 1998]. Furthermore, marsh edge erosion increases the mudflat area, which could be then eroded by surface erosion from bed shear stress. The model predicts that wave erosion would increase the suspended sediment concentration in the mudflat to 100–200 mg/L, which agrees with field measurements in the backbarrier basins of the Virginia Coast Reserve (VA, USA) [Lawson et al., 2007].
  • 21. Even when the marsh enters the runaway erosion and eventually disappears, the marsh platform keeps pace with sea level rise up to 10 mm/yr, i.e., marsh loss by drowning does not take place. Of particular notice is that the marsh platform keeps up even in the absence of an external sediment supply (co50). In this case, because the maximum accretion rate by organic sediment was set equal to 5 mm/yr, inorganic sediment contributed to 5 mm/yr of accretion or more. If only organic sediment were contributing to vertical accretion, a marsh starting at MHW (here set 1 m above msl) would have drown in 157 years considering a parabolic biomass-elevation relationship (see section 2.2) (Figure 9g). Where did the additional sediment come from if the external sediment concentration was zero? Clearly these sediment resulted from erosion of the basin, i.e., by internal recycling
  • 22. Equilibrium: ebb dominated currents that establish in channels with extensive intertidal areas No tidal flats => no marsh progradation
  • 23.
  • 24.
  • 25. remarkably similar, especially considering that the wave forcing is stochastic MF=400
  • 26.
  • 27.
  • 28. However, this formulation fails to reproduce the expected marsh edge retreat for a given wave power (equation (5)). For example, such a formulation predicts a fast (slow) edge retreat when the mudflat in front of the marsh is shallow deep), given that bed shear stress of locally generated waves decreases with water depth [Fagherazzi et al., 2006]. In reality, a faster marsh retreat is expected where the marsh edge faces a deeper mudflat, which would allow a larger wave power to reach the marsh edge.
  • 29. The ability of marshes to reduce sediment erodability and increase drag is simulated in a simplified way: if a cell is unvegetated the critical shear stress for erosion is set equal to scr,unveg and the Chezy coefficient for bed friction is set equal to Cunveg, if a cell is vegetated the critical shear stress is set equal to scr,veg and the Chezy coefficient is set equal to Cveg. Here we set the vegetated critical shear stress equal to 1 Pa, noticing that values above 0.8 Pa are already sufficient to make the soil virtually nonerodible [Marani et al., 2010]. This choice is consistent with the observation that the marsh platform is able to withstand large wave forces [M€oller, 2006]. s range from 2.5 mm/yr [D’Alpaos et al., 2007] to 10 mm/yr [Blum and Christian, 2004 The wave power causing marsh retreat is calculated on the unvegetated cell facing a marsh boundary cell as c is the specific weight of the water, Hs is the significant wave height, and cg is the wave group velocity, which are obtained from the SWAN model.
  • 30. marsh edge erosion is complex and poorly understood and includes a variety of masswasting geotechnical processes such as undercutting and cantilever failure, toppling failure, and stress failure, as well as hydrodynamic processes that occur at small spatial scales (0.1–1 m), such as wave breaking and dissipation over the edge [Schwimmer, 2001; McLoughlin et al., 2014; Priestas et al., 2015; Bendoni et al., 2016]. For simplicity, the effect of these processes are lumped into an empirical coefficient aw, which is highly variable, site specific, and not predictable a priori. Rather than selecting a value that fits a specific field site, we choose a value that gives marsh retreat rates on the order of a meter per year (see section 3.4), in range with field measurements Because of the large gird size (100 m) and the relatively small time step (2 min), the probability p is at most 1024 For the U.S. Atlantic Coast, organic matter contributes to about 50% to vertical accretion [Morris et al., 2016], therefore, we used a rounded value and set fox to 50% in our model
  • 31.
  • 32.
  • 33.
  • 34. Average marsh retreat rate during the first 100 years for the three rates of sea level rise. Given that the areal retreat rate is about 0.1 km2/yr for R51 mm/yr, 0.2 km2/yr for R55 mm/yr, and 0.4 km2/yr for R510 mm/yr (Figure 9a), and given that the total marsh edge perimeter during the same time is about 300 km (supporting information Figure S4),
  • 35.
  • 36. Thriving along protected shorelines, they are a common habitat in the U.S., where salt marshes can be found on every coast. Approximately half of the nation's salt marshes are located along the Gulf Coast. Salt marshes are coastal wetlands that are flooded and drained by salt water brought in by the tides. They are marshy because the soil may be composed of deep mud and peat. Back-barrier systems are coastal basins who are protected from storm by mean of barriers which are parallel to the coast. Salt marshes form in these relatively quiet environments, in which mud is allowed to deposit. Virginia Coast Reserve 3 – Long term evolution of back-barrier ecosystems: fill in or empty out?
  • 37. IMPORTANCE OF SALT MARSHES 3 – Long term evolution of back-barrier ecosystems: fill in or empty out? “The salt marsh is the most productive ecosystem known. Grasses, algae, and phyto-plankton can produce up to 10 tons of organic matter per acre per year. …Because more organic matter is produced than is used by salt marsh inhabitants, this community is continually exporting nutrients … enriching the surrounding estuary. The importance of the salt marsh to marine ecosystems cannot be overemphasized.” Janet McMahon in: “Forests, Fields, and Estuaries: A Guide to the Natural Communities of Josephine Newman Sanctuary”
  • 38. IMPORTANCE OF SALT MARSHES Act as effective storm buffer - withstand large wave forces with no significant vertical erosion - a reduction in wave height of 20% after crossing 40 metres. - Effective sediment trap In places where marshes have been destroyed, winter storms are more damaging. Erosive nature of tides is also dampened by wetland plants Tides carry in nutrients that stimulate plant growth in the marsh and carry out organic material that feeds fish and other coastal organisms Ability to filter out and break down toxins and sediments from incoming water. 3 – Long term evolution of back-barrier ecosystems: fill in or empty out? Salt marshes are important sinks for atmospheric CO2 Over time, salt marshes accumulate organic material, forming into a dense layer called peat. Moller et al. (2014)
  • 40. Distribution of Salt Marshes 3 – Salt marshes SUPPLEMENTARY MATERIAL
  • 41. Values of Korg used in previous models range from 2.5 mm/yr [D’Alpaos et al., 2007] to 10 mm/yr [Blum and Christian, 2004], here we choose an intermediate value of 5 mm/yr. 3 – Marshes SUPPLEMENTARY MATERIAL if a cell is unvegetated the critical shear stress for erosion is set equal to τcr,unveg and the Chezy coefficient for bed friction is set equal to Cunveg, if a cell is vegetated the critical shear stress is set equal to τcr,veg and the Chezy coefficient is set equal to Cveg. Here we set the vegetated critical shear stress equal to 1 Pa, noticing that values above 0.8 Pa are already sufficient to make the soil virtually nonerodible [Marani et al., 2010]. Such choice is consistent with the observation that the marsh platform is able to withstand large wave forces [Möller, 2006 𝑊 = 1 16 𝛾𝑐 𝑔 𝐻𝑠 2 " for conditions typical of the USA East Coast, organic matter probably contributes to about 60% to vertical accretion [Morris et al 2016], therefore we used a rounded value of 50%." VALUES USED IN THE MODEL
  • 42. 3 – Marshes SUPPLEMENTARY MATERIAL COMPARISON WITH LEONARDI AND FAGHERAZZI CELLULAR MODEL Note that a probabilistic approach has also been proposed in the context of a simple cellular automata model [Leonardi and Fagherazzi, 2014], which differs from our approach in many aspects. In Leonardi and Fagherazzi's approach, cells had no dimension and no bed elevation. Eroded material was not redistributed, therefore neglecting the dissipating effect that slumped blocks have on wave energy. Moreover, the erosion term was divided by the erosion rates in all the exposed edge of all the domain. This made the method global, which we think is not suitable for a physically based model. In fact, the erosion rate of a marsh cannot depend on the erosion rate on a different distal marsh, potentially located in a hydraulically disconnected region of the domain. Our method has the advantage to be local and it can be directly linked to the deterministic approach: the expected value of the erosion with the probabilistic method coincides with the erosion predicted with the deterministic method. Leonardi and Fagherazzi 2014
  • 43. 3 – Marshes SUPPLEMENTARY MATERIAL MODES OF MARSH EROSIONS UndercuttingSlumping
  • 44. Marsh emptying Channel widening is caused by waves, not currents co = 0 R = 1 mm/yr co = 30 mg/l R = 10 mm/yr 3 – Long term evolution of back-barrier ecosystems: fill in or empty out?
  • 45. 3 – Marshes SUPPLEMENTARY MATERIAL WAVE ENERGY IN THE BASIN Although sediment resuspension within channels is generally dominated by currents, our results show that current-induced bed shear stress is high only in the relatively narrow channels (Fig. 12). In the wide km-wide channels, wave-induced bed shear stress dominates, especially on channel flanks (Fig. 12). We therefore suggest that km-wide channels are needed to generate waves large enough to trigger wave-induced sediment resuspension.
  • 46. 3 – Marshes SUPPLEMENTARY MATERIAL
  • 47. Synthetic time series of wind speeds 3 – Marshes SUPPLEMENTARY MATERIAL Weibull probability distribution function for the hourly wind speed U is: where Uo is a scale parameter and b is a form parameter. Analysis of wind time series in the Atlantic and Gulf coastal areas of the US gave values of 1.9–2 for the form parameter b and 5.6–7.2 m/s for the scale parameter [Mariotti and Fagherazzi, 2012]. For an average wind speed of 5.76 m/s, corresponding values of 2 and 6.5 m/s for the form (distribuzione di Rayleigh) and the scale parameter were chosen. .
  • 48. Key West: The longer term trend computed by using all the data is +2.36 mm/year. Key west SLR 3 – Marshes SUPPLEMENTARY MATERIAL
  • 49. Take-home message • Edge erosion “empties” backbarrier basins • Retreat slowed down and reversed by external sediment supply, which promotes marsh progradation • Internal sediment recycle allow marsh to accrete vertically even in the absence of external sediment supply = • Sea level rise increases the rate of marsh retreat 3 – Long term evolution of back-barrier ecosystems: fill in or empty out? Low to moderate SLR(<5 mm/yr), such as those currently experienced in the US Atlantic Coast (Engelhart et al., 2009), marsh retreat is a more likely modality of marsh loss than marsh drowning!! • If no/low external sediment, basin can empty also with no SLR • “Filled basin” dynamic equilibrium with large channels
  • 50. 3 – Long term evolution of back-barrier ecosystems: fill in or empty out? Pagliaga salt marsh – Venice Lagoon Tidal meanders 1932 20121970 Gaggian creek
  • 52. 4 – Storm surge modeling and forecast Courtesy R. Scharroo – Altimetrics LLC Katrina: Satellite Altimeter Measurements
  • 53. The Delft3D model  =0 (water level=mean sea level) at Gibraltar Atmospherical forcings: ECMWF pressure fields ECMWF Wind velocity fields Small forecast error Large forecast error 4 – Storm surge modeling and forecast
  • 54. L The presence of a low atmospheric pressure event on the Northern part of the Tyrrhenian sea results in a South- Eastern wind (Scirocco) on the Adriatic sea A difference in atmospheric pressure of 1 hPA between the two extremities of the Adriatic sea produces a difference in the level of marine surface of approx. 1 cm! Main factors for storm surge in Venice: pressure differences and winds 4 – Storm surge modeling and forecast
  • 55. 4 – Storm surge modeling and forecast Forecast errors for storm larger than 50 cm (cross validation 2010-2011) Forecast Analysis Lead time (h)Lead time (h) MAE(cm)MAE(cm)
  • 56. DUD (Does not use derivatives) Delft3D is non linear!! (Ralston and Jennrich, Dud, A Derivative-Free Algorithm for Nonlinear Least Squares,1978) 4 – Storm surge modeling and forecast whereas the drag coefficient depends on both wind speed and wave state 8 wind directions plus 8 velocity intervals 64 parameters Model is strongly sensitive on the shear stress at the air-water interface I embedded in Cd the uncertainty on the velocity field and on Cd itself Cd is my calibration paramenter The goal is to find a vector of parameters xopt that minimizes: C Given: a set y of n observed data points a model prediction fi for the ith data point. a model with a vector x of p uncertain parameters
  • 57. • Application of storm surge satellite data to the coastal protection of Northern Cuba Luis Cordova, F. Reale, F. Dentale, R. Lamazares, M.Buccino, E. Pugliese Carratelli … • CUGRI (Universities of Naples &Salerno), and CUJAE (Instituto Superior Politécnico José Antonio Echeverría) of Havana 1) Evaluating different solutions for the protection of El Malecon (Sea front of Avana) 2) Simulating hurricane wave fields and storm surge 3) Acquiring and assessing satellite data to provide useful information for points 1 and 3 HurricaneIvan,2005
  • 58. 4– Surges - SUPPLEMENTARY MATERIAL DUD algorithm
  • 59. Take home message: Data assimilation largely improves storm surge forecast. An appropriate calibration of the model can remove its bias. Satellites provide a large amount of data which have to be assimilated efficiently in order to have real time predictions. But we need more satellite. Now the frequence at which satellites pass over the Adriatic Sea is once per day. 4– Surges - SUPPLEMENTARY MATERIAL